Desktop productivity applications typically provide many options for visualizing data. For instance, a spreadsheet application program may allow a user to select a column chart, a line chart, a pie chart, a bar chart, an area chart, a scatter chart, or another type of chart for visualizing the contents of a data set. Each type of chart can be used more or less effectively to represent the data in a given data set. As an example, a pie chart may be well suited for visualizing a certain data set while a scatter chart would not be well suited for visualizing the same data set.
In order to visualize a data set, a desktop productivity application program will generally ask a user to select one of the available visualization types. Making such a selection may be difficult, however, since many users will not know the visualization type that is best suited for their data set and may not know the range and extent of their own data. Many users may also be unaware of all of the visualization types that are available, especially where a large number of visualization types are provided or unusual or domain specific visualization types are available. As a result, it can be difficult for many users to choose a visualization type that is optimal for displaying their particular data set.
Once a user has selected a visualization type, it is also generally necessary to configure the visualization type for use with the data set. For instance, it is typically necessary to map columns of data within a data set to axes in the selected visualization type. In some cases the desktop productivity application may make basic assumptions about the data in order to automatically perform the mapping. If the application does not perform this function, or if the mapping generated by the application program is not optimal, the desktop productivity application may ask the user how the data in the data set should be mapped to the axes of the selected chart type. This also can be frustrating for a user that is not equipped to specify the most optimal mapping between the data in their data set and the selected visualization type.
It is with respect to these considerations and others that the disclosure made herein is presented.